A random forest can be considered a mechanism by which decision trees are formed. Random forest decision mechanisms have been an effective solution for computer security systems in that random forests are characterized by a combination of being both reasonably generic and accurate. Random forests are additionally fast to compile at runtime, in that the decision trees needs to only be interpreted once.
The problem random forest is the randomness—random forests treat all attributes equally and do not incorporate interrelationships between these attributes. As a result, random forest is a sub-optimum solution for use in malware detection.